Data Science Workflows
Course Structure, Admin and Expectations
Introductions and Definitions
Markdown, Git and Quarto
Mix of lecture, lab and group discussion.
Drop in Sessions: Fridays 15:00-17:00, Huxley 711C.
Office Hours: Mondays 15:00 - 16:00, Huxley 6M20.
Self-contained, text file, as small & simple as possible. Consider a Gist.
Which have you heard of before?
Which do you have experience of using?
What is data science to you and how does it relate to statistics?
What do you hope to get out of a data science course?
dplyr transition to SQLBefore Friday:
Follow Happy git with R instructions to link RStudio and Git and Github (§1-14).
Write a username/README.md introducing yourself on your GitHub profile and share in the discussion forum. (See e.g.: StatsRhian, nrennie)
Effective Data Science: Workflows - Organising Your Work - Zak Varty